detpack:Density Estimation and Random Number Generation with
Distribution Element Trees
Density estimation for possibly large data sets and conditional/unconditional random number generation or
bootstrapping with distribution element trees. The function
'det.construct' translates a dataset into a distribution
element tree. To evaluate the probability density based on a
previously computed tree at arbitrary query points, the
function 'det.query' is available. The functions 'det1' and
'det2' provide density estimation and plotting for one- and
two-dimensional datasets. Conditional/unconditional smooth
bootstrapping from an available distribution element tree can
be performed by 'det.rnd'. For more details on distribution
element trees, see: Meyer, D.W. (2016) <arXiv:1610.00345> or
Meyer, D.W., Statistics and Computing (2017)
<doi:10.1007/s11222-017-9751-9> and Meyer, D.W. (2017)
<arXiv:1711.04632> or Meyer, D.W., Journal of Computational and
Graphical Statistics (2018)
<doi:10.1080/10618600.2018.1482768>.
